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S. Olive, T. Welti, and O. Khonsaripour, "A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 2—Development and Validation of the Model," Paper 9878, (2017 October.). doi: S. Olive, T. Welti, and O. Khonsaripour, "A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 2—Development and Validation of the Model," Paper 9878, (2017 October.). doi:
Abstract: Part 1 of this paper presented the results of controlled listening tests where 71 listeners both trained and untrained gave preference ratings for 30 different models of in-ear (IE) headphones. Both trained and untrained listeners preferred the headphone equalized to Harman IE target curve. Objective measurements indicated the magnitude response of the headphone appeared to be a predictor of its preference rating, and the further it deviated from the response of the Harman IE target curve the less it was generally preferred. Part 2 presents a linear regression model that accurately predicts the headphone preference ratings (r = 0.91) based on the size, standard deviation and slope of the magnitude response deviation from the response of the Harman IE headphone target curve.

@article{olive2017a,
author={olive, sean and welti, todd and khonsaripour, omid},
journal={journal of the audio engineering society},
title={a statistical model that predicts listeners’ preference ratings of in-ear headphones: part 2—development and validation of the model},
year={2017},
volume={},
number={},
pages={},
doi={},
month={october},} @article{olive2017a,
author={olive, sean and welti, todd and khonsaripour, omid},
journal={journal of the audio engineering society},
title={a statistical model that predicts listeners’ preference ratings of in-ear headphones: part 2—development and validation of the model},
year={2017},
volume={},
number={},
pages={},
doi={},
month={october},
abstract={part 1 of this paper presented the results of controlled listening tests where 71 listeners both trained and untrained gave preference ratings for 30 different models of in-ear (ie) headphones. both trained and untrained listeners preferred the headphone equalized to harman ie target curve. objective measurements indicated the magnitude response of the headphone appeared to be a predictor of its preference rating, and the further it deviated from the response of the harman ie target curve the less it was generally preferred. part 2 presents a linear regression model that accurately predicts the headphone preference ratings (r = 0.91) based on the size, standard deviation and slope of the magnitude response deviation from the response of the harman ie headphone target curve.},}

TY - paper
TI - A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 2—Development and Validation of the Model
SP - EP -
AU - Olive, Sean
AU - Welti, Todd
AU - Khonsaripour, Omid
PY - 2017
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2017 TY - paper
TI - A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 2—Development and Validation of the Model
SP - EP -
AU - Olive, Sean
AU - Welti, Todd
AU - Khonsaripour, Omid
PY - 2017
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2017
AB - Part 1 of this paper presented the results of controlled listening tests where 71 listeners both trained and untrained gave preference ratings for 30 different models of in-ear (IE) headphones. Both trained and untrained listeners preferred the headphone equalized to Harman IE target curve. Objective measurements indicated the magnitude response of the headphone appeared to be a predictor of its preference rating, and the further it deviated from the response of the Harman IE target curve the less it was generally preferred. Part 2 presents a linear regression model that accurately predicts the headphone preference ratings (r = 0.91) based on the size, standard deviation and slope of the magnitude response deviation from the response of the Harman IE headphone target curve.